Submission

Put the ipynb file and html file in the github branch you created in the last assignment and submit the link to the commit in brightspace

In [31]:
from plotly.offline import init_notebook_mode
import plotly.io as pio
import plotly.express as px

init_notebook_mode(connected=True)
pio.renderers.default = "plotly_mimetype+notebook"
In [32]:
#load data
df = px.data.gapminder()
df.head()
Out[32]:
country continent year lifeExp pop gdpPercap iso_alpha iso_num
0 Afghanistan Asia 1952 28.801 8425333 779.445314 AFG 4
1 Afghanistan Asia 1957 30.332 9240934 820.853030 AFG 4
2 Afghanistan Asia 1962 31.997 10267083 853.100710 AFG 4
3 Afghanistan Asia 1967 34.020 11537966 836.197138 AFG 4
4 Afghanistan Asia 1972 36.088 13079460 739.981106 AFG 4

Question 1:

Recreate the barplot below that shows the population of different continents for the year 2007.

Hints:

  • Extract the 2007 year data from the dataframe. You have to process the data accordingly
  • use plotly bar
  • Add different colors for different continents
  • Sort the order of the continent for the visualisation. Use axis layout setting
  • Add text to each bar that represents the population
In [33]:
df_2007 = df.query('year==2007')
a = df_2007.groupby('continent')
df_2007_new = df_2007.groupby('continent').sum()
fig = px.bar(df_2007_new, x="pop", y=df_2007_new.index , color =df_2007_new.index, orientation='h', text_auto = True)
fig.update_yaxes(categoryorder="min ascending")
fig.show()

Question 2:

Sort the order of the continent for the visualisation

Hint: Use axis layout setting

In [34]:
df_2007 = df.query('year==2007')
a = df_2007.groupby('continent')
df_2007_new = df_2007.groupby('continent').sum()
fig = px.bar(df_2007_new, x="pop", y=df_2007_new.index , color =df_2007_new.index, orientation='h', text_auto = True)
fig.update_yaxes(categoryorder="min ascending")
fig.show()

Question 3:

Add text to each bar that represents the population

In [35]:
df_2007 = df.query('year==2007')
a = df_2007.groupby('continent')
df_2007_new = df_2007.groupby('continent').sum()
fig = px.bar(df_2007_new, x="pop", y=df_2007_new.index , color =df_2007_new.index, orientation='h', text_auto = True)
fig.update_yaxes(categoryorder="min ascending")
fig.show()

Question 4:

Thus far we looked at data from one year (2007). Lets create an animation to see the population growth of the continents through the years

In [36]:
fig = px.bar(df, y='continent', x='pop', color='continent', animation_frame='year', animation_group='country', range_x=[0, 4000000000])
fig.update_yaxes(categoryorder="total ascending")
fig.show()

Question 5:

Instead of the continents, lets look at individual countries. Create an animation that shows the population growth of the countries through the years

In [37]:
fig = px.bar(df, y='country', x='pop', color='country', animation_frame='year', animation_group='country', range_x=[0, 4000000000])
fig.update_yaxes(categoryorder="total ascending")
fig.show()

Question 6:

Clean up the country animation. Set the height size of the figure to 1000 to have a better view of the animation

In [38]:
fig = px.bar(df, y='country', x='pop', color='country', animation_frame='year', animation_group='country', range_x=[0, 4000000000], height =2500)
fig.update_yaxes(categoryorder="total ascending")
fig.show()

Question 7:

Show only the top 10 countries in the animation

Hint: Use the axis limit to set this.

In [39]:
fig = px.bar(df, y='country', x='pop', color='country', animation_frame='year', animation_group='country', range_x=[0, 4000000000])
fig.update_yaxes(categoryorder="total descending", range = [-0.5,10.5])
fig.show()